You put your AI agent in a container. You put the container in Kubernetes. You added network policies and RBAC. Then an exec asked it to build a sentiment analysis model and it escalated its way through your entire cloud account. Here's exactly how.
Too many architecture reviews are just debates about which vendor's service logo to put on the diagram. The real value of an architect is knowing when the menu is the wrong starting point.
A thousand tiny Lambda functions scattered everywhere with no ownership, no contracts, and no way to test them locally. Sound familiar? Here's when serverless works, when it doesn't, and the discipline most teams skip.
Most Kubernetes comparisons are feature matrices written by people who've read the docs. This is what the three major managed Kubernetes services actually feel like when you're running production workloads, handling upgrades at 2am, and arguing with IAM policies.
The Infrastructure as Code wars are over. Terraform won. And yet enterprise teams are still clinging to vendor-native tooling like ARM templates and CloudFormation because 'it's supported by the vendor.' Supported doesn't mean good.
Nobody is running workloads portably across clouds. They're running different things on different clouds and calling it a strategy. Multi-cloud is what happens when nobody's in charge.